DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilistic Model (DDPM)-based approaches have shown promise by equipping the dif- fusion process with pretrained mean and variance estimators to accommodate distributional shif...
Wei-Wei Ye, Dong-Yuan Li, Hang-Chen Liu et al.
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